code: def custom_eval_shared_model(
      eval_saved_model_path, model_name, eval_config, **kwargs
  ) -> tfma.EvalSharedModel:
      """Returns a single custom EvalSharedModel."""
      model_path = os.path.join(eval_saved_model_path, "model.pkl")
      return tfma.default_eval_shared_model(
          eval_saved_model_path=model_path,
          model_name=model_name,
          eval_config=eval_config,
          custom_model_loader=tfma.ModelLoader(
              construct_fn=_custom_model_loader_fn(model_path)
          ),
          add_metrics_callbacks=kwargs.get("add_metrics_callbacks"),
      )
  
file_path: tfx/tfx/examples/penguin/experimental/sklearn_predict_extractor.py
imports: import copy
  import os
  import pickle
  from typing import Dict, Iterable, List
  import apache_beam
  import tensorflow
  import tensorflow_model_analysis
  from tfx_bsl.tfxio import tensor_adapter
label_desc: Use image node_id 4 for calling a global function with example usage: custom_eval_shared_model(eval_saved_model_path, model_name, eval_config) and returns: tfma